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70.78/100

前 2.5%

全站排名 #1,607

发表论文10 篇

平均评分6.1

年均产出3.3 篇/年

David Rügamer

Associate Professor@LMU Munich·德国·OpenReview

研究方向

Scalable Additive Models · Sparse Neural Networks · Bayesian Neural Networks · Sampling-based Inference · Probabilistic Machine Learning

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

ICLR 2026Rejected

Differentiable Sparsity via $D$-Gating: Simple and Versatile Structured Penalization

NeurIPS 2025Spotlight

Calibrating LLMs with Information-Theoretic Evidential Deep Learning

ICLR 2025Poster

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries

ICLR 2025Poster

Revisiting Unbiased Implicit Variational Inference

ICML 2025Poster

In-Context Learning for Full Bayesian Inference

ICLR 2025Rejected

Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks

ICLR 2025Poster

Adjustment for Confounding using Pre-Trained Representations

ICML 2025Poster

Can Transformers Learn Full Bayesian Inference in Context?

ICML 2025Poster

合作者 (20)

PhD Advisee2 篇

Tim G. J. Rudner

Vincent Fortuin

PhD Advisee2 篇